I develop an agency model where returns-chasing behavior by mutual fund investors causes beta not to be priced to the degree predicted by the standard CAPM. Mutual fund investors chase returns through time, precipitating unusually large aggregate cash inflows into mutual funds just after dramatic market runups. Mutual fund investors also chase returns cross-sectionally across funds so that the highest-performing funds capture the largest fraction of the aggregate inflows into the mutu al fund sector. The interaction of these two flow-performance relationships induces an asymmetry in payoffs to mutual funds where fund managers care most about outperforming peers during bull markets. Since high-beta stocks tend to outperform in up markets, active fund managers tilt their portfolios toward high-beta stocks, reducing the beta risk premium in equilibrium. To support the model's time-series flow-performance assumption, I show empirically that market returns have a large economic impact on subsequent aggregate mutual fund flows. In addition, data on mutual fund holdings suggest that the aggregate stock portfolio held by equity funds is overweighted in high-beta stocks relative to the overall market, though this does not include the cash held by mutual funds. Fama-MacBeth tests indicate that the equity premium falls only slightly as the relative size of mutual funds increases, and the relation is not statistically significant.

Firms with poor aftermarket performance are given higher target prices and are more likely to receive strong buy recommendations, especially by analysts affiliated with the lead underwriter. This favorable coverage is relatively short lived, typically lasting less than six months. Controlling for the quantity of coverage received, stock prices of newly public firms increase more when the target price ratio is high and recommendation is a strong buy. These results suggest that when a firm goes public, underwriter-affiliated analysts provide protection in the form of “booster shots” of stronger coverage if the firm experiences poor aftermarket stock performance.

Analysts' earnings forecasts are influenced by their desire to win investment banking clients. We hypothesize that the equity bull market of the 1990s, along with the boom in investment banking business, exacerbated analysts' conflicts of interest and their incentives to strategically adjust forecasts to avoid earnings disappointments. We document shifts in the distribution of earnings surprises and related changes in the market's response to surprises and forecast revisions. The evidence for shifts is stronger for growth stocks, where conflicts of interest are more pronounced. However, shifts are less notable for analysts without ties to investment banking and in international markets.

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We evaluate the performance of models for the covariance structure of stock returns, focusing on their use for optimal portfolio selection. We compare the models' forecasts of future covariances and the optimized portfolios' out-of-sample performance. A few factors capture the general covariance structure. Portfolio optimization helps for risk control, and a three-factor model is adequate for selecting the minimum-variance portfolio. Under a tracking error volatility criterion, which is widely used in practice, larger differences emerge across the models. In general more factors are necessary when the objective is to minimize tracking error volatility.

[We evaluate the performance of models for the covariance structure of stock returns, focusing on their use for optimal portfolio selection. We compare the models' forecasts of future covariances and the optimized portfolios' out-of-sample performance. A few factors capture the general covariance structure. Portfolio optimization helps for risk control, and a three-factor model is adequate for selecting the minimum-variance portfolio. Under a tracking error volatility criterion, which is widely used in practice, larger differences emerge across the models. In general more factors are necessary when the objective is to minimize tracking error volatility.]

A number of mutual funds cater exclusively to institutional investors. Although institutional funds might be a natural place to look for “smart money”, agency costs associated with delegated monitoring may lead to less monitoring and worse overall performance. We split institutional funds based on proxies for the degree of investor oversight, and we find that institutional funds with low initial investment requirements and funds with retail mates perform significantly worse than other institutional funds both before and after adjusting for risk and expenses. Tracking error is especially important in the flow-performance relationship of institutional funds with high minimum investment requirements.

ABSTRACT Expectations about long‐term earnings growth are crucial to valuation models and cost of capital estimates. We analyze historical long‐term growth rates across a broad cross section of stocks using several indicators of operating performance. We test for persistence and predictability in growth. While some firms have grown at high rates historically, they are relatively rare instances. There is no persistence in long‐term earnings growth beyond chance, and there is low predictability even with a wide variety of predictor variables. Specifically, IBES growth forecasts are overly optimistic and add little predictive power. Valuation ratios also have limited ability to predict future growth.

We examine how analysts establish target prices for IPO firms and whether comparable firms used to support target prices are helpful in explaining IPO offer prices. During the bubble period of 1999 to 2000, the average offer price was set at a discount relative to comparable firm valuations. In contrast, the average offer price was set at a small premium relative to comparables in the pre-bubble period. This shift appears to hold even after controlling for the differences in the types of firms going public during the bubble period. Moreover, target prices of IPO firms were set at a higher premium relative to comparables during the bubble period. While our results suggest that underwriters systematically discounted offer prices during the bubble period, an alternative explanation is that the shift arose because underwriters and analysts faced different incentives and legal exposures during the bubble period.

ABSTRACT We estimate the impact of bank merger announcements on borrowers' stock prices for publicly traded Norwegian firms. Borrowers of target banks lose about 0.8% in equity value, while borrowers of acquiring banks earn positive abnormal returns, suggesting that borrower welfare is influenced by a strategic focus favoring acquiring borrowers. Bank mergers lead to higher relationship exit rates among borrowers of target banks. Larger merger‐induced increases in relationship termination rates are associated with less negative abnormal returns, suggesting that firms with low switching costs switch banks, while similar firms with high switching costs are locked into their current relationship.